How to Become a Data Scientist for Free!

Big Data, Data Sciences, and Predictive Analytics are the talk of the town and it doesn’t matter which town you are referring to, it’s everywhere, from the White House hiring DJ Patil as the first chief data scientist to the United Nations using predictive analytics to forecast bombings on schools. There are dozens of Startups springing out every month stretching human imagination of how the underlying technologies can be used to improve our lives and everything we do. Data science is in demand and its growth is on steroids. According to Linkedin, “Statistical Analysis” and “Data Mining” are two top-most skills to get hired this year. Gartner says there are 4.4 million jobs for data scientists (and related titles) worldwide in 2015, 1.9 million in the US alone. One data science job creates another three non-IT jobs, so we are talking about some 13 million jobs altogether. The question is what YOU can do to secure a job and make your dreams come true, and how YOU can become someone that would qualify for these 4.4 million jobs worldwide.

There are at least 50 data science degree programs by universities worldwide offering diplomas in this discipline, it costs from 50,000 to 270,000 US$ and takes 1 to 4 years of your life. It might be a good option if you are looking to join college soon, and it has its own benefits over other programs in similar or not-to-so similar disciplines. I find these programs very expensive for the people from developing countries or working professionals to commit X years of their lives.

Then there are few very good summer programs, fellowships and boot camps that promise you to make a data scientists in very short span of time, some of them are free but almost impossible to get in, while other requires a PhD or advanced degree, and some would cost between 15,000 to 25,000 US$ for 2 months or so. While these are very good options for recent Ph.D. graduates to gain some real industry experience, we have yet to see their quality and performance against a veteran industry analyst. Few of the ones that I really like are Data Incubator, Insight Fellowship, Metis Bootcamp, Data Science for Social Goods and the famous Zipfian Academy programs.

Let me also mention few paid resources that I am a fan of before I tell you how to do all that for free. First one is the Explore Data Science program by Booz Allen, it costs 1,250 $ but worth a single penny. Second one is recorded lectures by Tim Chartier on DVD, called Big Data: How Data Analytics is transforming the world, it costs 80 bucks and worth your investment. The next in the list are two courses by MIT, Tackling the Big Data Challenges, that costs 500$ and provides you a very solid theoretical foundation on big data, and The Analytics Edge, that costs only 100 bucks and gives a superb introduction on how the analytics can be used to solve day-to-day business problems. If you can spare few hours a day then Udacity offers a perfect Nanodegree for Data Analysts that costs 200$/month can be completed in 6 months or so, they offer this in partnership with Facebook, Zipfian Academy, and MongoDB. ThinkFul has a wonderful program for 500$/month to connect you live with a mentor to guide you to become a data scientist.

Ok, so what one can do to become a data scientist if he/she cannot afford or get selected in the aforementioned competitive and expensive programs. What someone from a developing country can do to improve his/her chances of getting hired in this very important field or even try to use these advanced skills to improve their own surroundings, communities and countries.

Here is my cheat sheet of becoming a Data Scientist for Free:

Understand Data: Data is useless and can (and should) be misleading without the context. Data needs a story to tell a story. Data is like a color that needs a surface to even prove its existence, as color red for example, can’t prove its existence without a surface, we see a red car, or red scarf, red tie, red shoes or red something, similarly data needs to be associated with its surroundings, context, methods, ways and the whole life cycle where it is born, generated, used, modified, executed and terminated. I have yet to find a “data scientist” who can talk to me about the “data” without mentioning technologies like Hadoop, NoSQL, Tableau or other sophisticated vendors and buzzwords. You need to have an intimate relationship with your data; you need to know it inside out. Asking someone else about anomalies in “your” data is equal to asking your wife how she gets pregnant. One of the distinct edge we had for our relationship with the UN and the software to secure schools form bombings is our command over the underlying data, while the world talks about it using statistical charts and figures, we are the ones back home who experience it, live it in our daily lives, the importance, details, and the appreciation of this data that we have cannot be find anywhere else. We are doing the same with our other projects and clients.

Understand Data Scientist: Unfortunately, one of the most confused and misused word in data sciences filed is the “data scientist” itself. Someone relate it to a mystic oracle who would know everything under the sun, while others would reduce it down to statistical expert, for few its someone familiar with Hadoop and NoSQL, and for others it is someone who can perform A/B testing and can use so much mathematics and statistical terms that would be hard to understand in executive meetings. For some, it is visualization dashboards and for others it’s a never ending ETL processes. For me, a Data Scientist is someone who understands less about the science than the ones who creates it and little less about the data than the ones who generates it, but exactly knows how these two works together. A good data scientist is the one who knows what is available “outside the box” and who he needs to connect with, hire, or the technologies he needs to deploy to get the job done, one who can link business objectives with data marts, and who can simply connect the dots from business gains to human behaviors and from data generation to dollars spent.

The whole list will take 3 to 12 months to complete and will cost you absolutely nothing, and I can guarantee you that with this skills set you really have to try very hard to remain jobless. Even if you complete half of it, send me a note and I will have something ready for you.

Ball is in your court, it doesn’t matter where you are and how much you can afford, if you want to make at least four times higher the average income of your countrymen, this is the way to do it, at least for next 10 years (where we will be generating 20 TBs of data per year per person versus 1 TB of data per year per person in the last 10 years.)

I will write separate articles on Data Science Books (I’ve read 127 of those in last six months) and MOOCs (I am celebrating my 25th MOOC certification today).

For everyone else data sciences is an opportunity, for me it’s a passion